mutate() vs summarise()

Better alternatives to bar plots

Bar plots are typically reserved for displaying frequencies

# A tibble: 4 × 3
  geography     mean_price_diff sd_price_diff
  <fct>                   <dbl>         <dbl>
1 San Francisco           0.719         0.334
2 San Diego               0.685         0.211
3 Sacramento              0.578         0.270
4 Los Angeles             0.528         0.188

library(RColorBrewer)
library(scales)

diff_summary  |> 
  ggplot(aes(x = mean_price_diff, 
             y = geography,
             fill = geography)
         ) +
  geom_bar(stat = "identity") +
  labs(
    title = "Difference in Price between Organic and Conventional Avocados",
    y = "") +
  theme_minimal() +
  theme(legend.position = "none") +
  scale_fill_brewer(palette = "Dark2") +
  scale_x_continuous(name = "", 
                     labels = scales::label_dollar()
                     )

diff_summary |> 
  arrange(desc(mean_price_diff)) |> 
  ggplot(aes(x = mean_price_diff, 
             y = geography,
             fill = geography)
         ) +
  geom_segment(aes(xend = 0,
                   yend = geography)
  ) +
  geom_point() +
  labs(title = "Difference in Price between Organic and Conventional Avocados",
       y = "") +
  theme_minimal() +
  theme(legend.position = "none") +
  scale_fill_brewer(palette = "Dark2") + 
  scale_x_continuous(name = "", 
                     labels = scales::label_dollar()
                     )

Little Bits and Bobs

hiphop %>% 
  distinct(subj, .keep_all = TRUE) %>%
  filter(sex == "Male" & 
         between(age, 17, 23) &
         between(city, 10000, 60000)
         ) %>%
  slice_max(bieber) %>%
  select(subj)

avocado %>% 
  rename(Size_Small = `4046`) %>% 
  rename(Size_Large = `4225`) %>% 
  rename(Size_XL = `4770`)

Git vs GitHub

Why GitHub?

1. A structured way for tracking changes to files over the course of a project.

2. Makes it easy to have multiple people working on the same files at the same time.

3. You can host a URL of fun things (like the class text, these slides, a personal website, etc.) with GitHub pages.

Think “track-changes” or “drop-box” history, but more structured.

Git Repositories

• Think of this as a folder-directory for a single project (like your stat-331 folder!)

• You may have code, documentation, data, TODO lists, and more associated with a project.

• To create a repository, you can start with your local computer first, or you can start with the remote (online) repository first.

Cloning a Repo

Committing

Git tracks changes to each file that it is told to monitor, and as the files change, you provide short labels describing what the changes were and why they exist (called “commits”).

The log of these changes (along with the file history) is called your git commit history. This means you can always go back to old copies!

Pushing

Pulling

Pushing and Pulling

Merge Conflicts

Occur when you make changes to the same line as a collaborator either at the same time, or without starting from the same “state”.

1. Maybe you are working in real time on the same line of code or text.
2. Maybe you forgot to push your changes last time you finished working.
3. Maybe you forgot to pull your changes before you started working this time.

Workflow

Workflow

Rpackages we will need

Work in your terminal or an .Rscript for this…

1. Install and load the {usethis} Rpackage

install.packages(usethis)
library(usethis)

2. Install and load {gitcreds} RPackage

install.packages("gitcreds")
library(gitcreds)

Generate your PAT (Personal Access Token)

create_github_token()

Store your PAT

4. Copy your PAT into RStudio

5. Enter password or token: Paste PAT

gitcreds_set()

Verify PAT

You should be good to go! Let’s verify.

git_sitrep()

Tips for avoiding merge conflicts

Forking a Repository

Fork the STAT331_portfolio_template repository

Create a New RStudio Project

Save Your Project

Do not save your project in the same folder as your STAT331.Rproj!!!!